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PubMed1999

Phylogenetic evidence for horizontal transmission of Wolbachia in host-parasitoid associations.

Endosymbiotic Wolbachia infect a number of arthropod species in which they can affect the reproductive system. While maternally transmitted, unlike mitochondria their molecular phylogeny does not parallel that of their hosts. This strongly suggests horizontal transmission among species, the mechanisms of which remain unknown. Such transfers require intimate between-species relationships, and thus host-parasite associations are outstandingly appropriate for study. Here, we demonstrate that hymenopteran parasitoids of frugivorous Drosophila species are especially susceptible to Wolbachia infection. Of the five common European species, four proved to be infected; furthermore, multiple infections are common, with one species being doubly infected and two triply infected (first report). Phylogenetic statuses of the Wolbachia infecting the different species of the community have been studied using the gene wsp, a highly variable gene recently described. This study reveals exciting similarities between the Wolbachia variants found in parasitoids and their hosts. These arguments strongly support the hypothesis of frequent natural Wolbachia transfers into other species and open a new field for genetic exchanges among species, especially in host-parasitoid associations.

Animals↗
PubMed2000

Mining medical data.

Explore the source record for details and available documents.

Data Interpretation, Statistical↗
PubMed2005

MASQOT: a method for cDNA microarray spot quality control.

BACKGROUND: cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more. RESULTS: A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies. CONCLUSION: The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process.

Data Interpretation, Statistical↗
PubMed2003

The temperature dependence of gramicidin conformational States in octanol.

In lipid bilayers and organic solvents, the hydrophobic polypeptide gramicidin adopts a number of different conformations, some of which are capable of conducting monovalent cations across phospholipid membranes. The equilibria between conformations have been shown to be influenced by factors such as lipid chain length, solvent, concentration and salt. In this study, the temperature dependence of the equilibrium mixture of double helical ion-free gramicidin in octanol was examined using circular dichroism spectroscopy.

Amino Acid Sequence↗
PubMed1999

Unsupervised classification of Space Acceleration Measurement System (SAMS) data using ART2-A.

The Space Acceleration Measurement System (SAMS) has been developed by NASA to monitor the microgravity acceleration environment aboard the space shuttle. The amount of data collected by a SAMS unit during a shuttle mission is in the several gigabytes range. Adaptive Resonance Theory 2-A (ART2-A), an unsupervised neural network, has been used to cluster these data and to develop cause and effect relationships among disturbances and the acceleration environment. Using input patterns formed on the basis of power spectral densities (psd), data collected from two missions, STS-050 and STS-057, have been clustered.

Acceleration↗
PubMed2003

Effects of distortions by A-tracts of promoter B-DNA spacer region on the kinetics of open complex formation by Escherichia coli RNA polymerase.

A-tracts in DNA due to their structural morphology distinctly different from the canonical B-DNA form play an important role in specific recognition of bacterial upstream promoter elements by the carboxyl terminal domain of RNA polymerase alpha subunit and, in turn, in the process of transcription initiation. They are only rarely found in the spacer promoter regions separating the -35 and -10 recognition hexamers. At present, the nature of the protein-DNA contacts formed between RNA polymerase and promoter DNA in transcription initiation can only be inferred from low resolution structural data and mutational and crosslinking experiments. To probe these contacts further, we constructed derivatives of a model Pa promoter bearing in the spacer region one or two An (n = 5 or 6) tracts, in phase with the DNA helical repeat, and studied the effects of thereby induced perturbation of promoter DNA structure on the kinetics of open complex (RPo) formation in vitro by Escherichia coli RNA polymerase. We found that the overall second-order rate constant ka of RPo formation, relative to that at the control promoter, was strongly reduced by one to two orders of magnitude only when the A-tracts were located in the nontemplate strand. A particularly strong 30-fold down effect on ka was exerted by nontemplate A-tracts in the -10 extended promoter region, where an involvement of nontemplate TG (-14, -15) sequence in a specific interaction with region 3 of sigma-subunit is postulated. A-tracts in the latter location caused also 3-fold slower isomerization of the first closed transcription complex into the intermediate one that precedes formation of RPo, and led to two-fold faster dissociation of the latter. All these findings are discussed in relation to recent structural and kinetic models of RPo formation.

Base Sequence↗
PubMed1994

Health management in herds.

In this paper, the general process of health management and disease prevention at the herd level is described. The important steps include data collection, calculation of performance parameters, decision making, data analysis, problem definition, and finally installing preventive and therapeutic measures. Important components of a successful health management program include reliable data collection, automated data analysis, excellent veterinary clinical skills, and knowledge of epidemiological methods.

Animal Husbandry↗
PubMed1989

Analysis of surveillance data: a rationale for statistical tests with comments on confidence intervals and statistical models.

In the examination of differences between subgroups in surveillance data, whether through simple counting or through sophisticated statistical modelling, the comparison is not between simple random samples from two or more populations. The rationale for statistical tests rests on an appeal to a model of random permutation of demographic and disease factors for the observed population during the surveillance period. The testing evaluates chance as a possible explanation for the observed results. In the analysis of internal structure in a surveillance data set, statistical tests produce a conceptually simple result that lends itself to concise presentation and flexible interpretation. Tests limit emphasis on probabilistic manipulation and on parameter estimates. They cannot stand alone, and thus encourage descriptive presentation of observations. In contrast, statistical models and confidence intervals emphasize parameters rather than distributions and compete with the data for limited space.

Data Interpretation, Statistical↗
PubMed2004

Understanding data in clinical research: a simple graphical display for plotting data (up to four independent variables) after binary logistic regression analysis.

In clinical research, suitable visualization techniques of data after statistical analysis are crucial for the researches' and physicians' understanding. Common statistical techniques to analyze data in clinical research are logistic regression models. Among these, the application of binary logistic regression analysis (LRA) has greatly increased during past years, due to its diagnostic accuracy and because scientists often want to analyze in a dichotomous way whether some event will occur or not. Such an analysis lacks a suitable, understandable, and widely used graphical display, instead providing an understandable logit function based on a linear model for the natural logarithm of the odds in favor of the occurrence of the dependent variable, Y. By simple exponential transformation, such a logit equation can be transformed into a logistic function, resulting in predicted probabilities for the presence of the dependent variable, P(Y-1/X). This model can be used to generate a simple graphical display for binary LRA. For the case of a single predictor or explanatory (independent) variable, X, a plot can be generated with X represented by the abscissa (i.e., horizontal axis) and P(Y-1/X) represented by the ordinate (i.e., vertical axis). For the case of multiple predictor models, I propose here a relief 3D surface graphic in order to plot up to four independent variables (two continuous and two discrete). By using this technique, any researcher or physician would be able to transform a lesser understandable logit function into a figure easier to grasp, thus leading to a better knowledge and interpretation of data in clinical research. For this, a sophisticated statistical package is not necessary, because the graphical display may be generated by using any 2D or 3D surface plotter.

Biomedical Research↗
PubMed1989

Philosophers assess randomized clinical trials: the need for dialogue.

In recent years a growing number of professional philosophers have joined in the controversy over ethical aspects of randomized clinical trials (RCTs). Morally questionable in their utilitarian approach, RCTs are claimed by some to be in direct violation of the second form of Kant's Categorical Imperative. But the arguments used in these critiques at times derive from a lack of insight into basic statistical procedures and the realities of the biomedical research process. Presented to physicians and other nonspecialists, including the lay public, such distortions can be harmful. Given the great complexity of statistical methodology and the anomalous nature of concepts of evidence, more sustained input into the interdisciplinary dialogue is needed from the statistical profession.

Comprehension↗
PubMed1999

Commentary: On the limited role of the "single-subject" design in psychology: hypothesis generating but not testing.

The "single-subject" design (which really denotes a design that employs too few subjects to allow statistical inferences concerning significance to be made) is useful only for the generation, but not for the testing or evaluation, of hypotheses concerning any psychological function. Those hypotheses that may be suggested by the "single-subject" design include ones about within-subject developmental effects (which may need to be studied over multiple sessions), as well as individual-difference-related variables. To adequately test any of those hypotheses, however, it is necessary to employ designs that vary both within- and between-subject factors, and that also examine various correlations in such a way that all effects (including correlational ones) can be evaluated by conventional modes of statistical inference.

Data Interpretation, Statistical↗
PubMed1999

[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].

PURPOSE: To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. MATERIALS AND METHODS: The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. RESULTS: 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. CONCLUSIONS: During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.

Data Interpretation, Statistical↗
PubMedDate not supplied

Understanding the research methodology: should we trust the researchers' conclusions?

Understanding the methodology section of research articles is difficult for those unfamiliar with research design, but is essential for judging the credibility of the researchers' findings. The methodology section describes measures taken to avoid reaching the wrong conclusions. When comparing two or more treatments, researchers might find a difference in treatments when none exists (type I error) or not find a difference when there actually is one (type II error). Type I errors are minimized by random assignment to treatment and control groups, double blinding, ensuring that the treatment under study is the only difference between groups, and setting the level of significance in advance. Type II errors are minimized by using an adequately sized, homogenous sample, increasing the treatment strength, measuring precisely, and using appropriate statistics. The purpose of this article is to explain these common experimental strategies and statistical terms.

Bias↗